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Systemic lupus erythematous (SLE) is a heterogeneous autoimmune disease in which outcomes vary among different racial groups. Here, we aim to identify SLE subgroups within a multiethnic cohort using an unsupervised clustering approach based on the American College of Rheumatology (ACR) classification criteria. We identify three patient clusters that vary according to disease severity. Methylation association analysis identifies a set of 256 differentially methylated CpGs across clusters, including 101 CpGs in genes in the Type I Interferon pathway, and we validate these associations in an external cohort. A cis-methylation quantitative trait loci analysis identifies 744 significant CpG-SNP pairs. The methylation signature is enriched for ethnic-associated CpGs suggesting that genetic and non-genetic factors may drive outcomes and ethnic-associated methylation differences. Our computational approach highlights molecular differences associated with clusters rather than single outcome measures. This work demonstrates the utility of applying integrative methods to address clinical heterogeneity in multifactorial multi-ethnic disease settings.

High costs and technical limitations of cell sorting and single-cell techniques currently restrict the collection of large-scale, cell-type-specific DNA methylation data. This, in turn, impedes our ability to tackle key biological questions that pertain to variation within a population, such as identification of disease-associated genes at a cell-type-specific resolution. Here, we show mathematically and empirically that cell-type-specific methylation levels of an individual can be learned from its tissue-level bulk data, conceptually emulating the case where the individual has been profiled with a single-cell resolution and then signals were aggregated in each cell population separately. Provided with this unprecedented way to perform powerful large-scale epigenetic studies with cell-type-specific resolution, we revisit previous studies with tissue-level bulk methylation and reveal novel associations with leukocyte composition in blood and with rheumatoid arthritis. For the latter, we further show consistency with validation data collected from sorted leukocyte sub-types.

ObjectiveOnset of multiple sclerosis (MS) occurs in childhood for approximately 5% of cases (pediatric MS, or ped-MS). Epigenetic influences are strongly implicated in MS pathogenesis in adults, including the contribution from microRNAs (miRNAs), small noncoding RNAs that affect gene expression by binding target gene mRNAs. Few studies have specifically examined miRNAs in ped-MS, but individuals developing MS at an early age may carry a relatively high burden of genetic risk factors, and miRNA dysregulation may therefore play a larger role in the development of ped-MS than in adult-onset MS. This study aimed to look for evidence of miRNA involvement in ped-MS pathogenesis.MethodsGWAS results from 486 ped-MS cases and 1362 controls from the U.S. Pediatric MS Network and Kaiser Permanente Northern California membership were investigated for miRNA-specific signals. First, enrichment of miRNA-target gene network signals was evaluated using MIGWAS software. Second, SNPs in miRNA genes and in target gene binding sites (miR-SNPs) were tested for association with ped-MS, and pathway analysis was performed on associated target genes.ResultsMIGWAS analysis showed that miRNA-target gene signals were enriched in GWAS (P = 0.038) and identified 39 candidate biomarker miRNA-target gene pairs, including immune and neuronal signaling genes. The miR-SNP analysis implicated dysregulation of miRNA binding to target genes in five pathways, mainly involved in immune signaling.InterpretationEvidence from GWAS suggests that miRNAs play a role in ped-MS pathogenesis by affecting immune signaling and other pathways. Candidate biomarker miRNA-target gene pairs should be further studied for diagnostic, prognostic, and/or therapeutic utility.

Multiple sclerosis (MS) is an autoimmune disease with high prevalence among populations of northern European ancestry. Past studies have shown that exposure to ultraviolet radiation could explain the difference in MS prevalence across the globe. In this study, we investigate whether the difference in MS prevalence could be explained by European genetic risk factors. We characterized the ancestry of MS-associated alleles using RFMix, a conditional random field parameterized by random forests, to estimate their local ancestry in the largest assembled admixed population to date, with 3,692 African Americans, 4,915 Asian Americans, and 3,777 Hispanics. The majority of MS-associated human leukocyte antigen (HLA) alleles, including the prominent HLA-DRB1*15:01 risk allele, exhibited cosmopolitan ancestry. Ancestry-specific MS-associated HLA alleles were also identified. Analysis of the HLA-DRB1*15:01 risk allele in African Americans revealed that alleles on the European haplotype conferred three times the disease risk compared to those on the African haplotype. Furthermore, we found evidence that the European and African HLA-DRB1*15:01 alleles exhibit single nucleotide polymorphism (SNP) differences in regions encoding the HLA-DRB1 antigen-binding heterodimer. Additional evidence for increased risk of MS conferred by the European haplotype were found for HLA-B*07:02 and HLA-A*03:01 in African Americans. Most of the 200 non-HLA MS SNPs previously established in European populations were not significantly associated with MS in admixed populations, nor were they ancestrally more European in cases compared to controls. Lastly, a genome-wide search of association between European ancestry and MS revealed a region of interest close to the ZNF596 gene on chromosome 8 in Hispanics; cases had a significantly higher proportion of European ancestry compared to controls. In conclusion, our study established that the genetic ancestry of MS-associated alleles is complex and implicated that difference in MS prevalence could be explained by the ancestry of MS-associated alleles.

BackgroundStrong evidence supports the role of both genetic and environmental factors in pediatric-onset multiple sclerosis (POMS) etiology.ObjectiveWe comprehensively investigated the association between established major histocompatibility complex (MHC) and non-MHC adult multiple sclerosis (MS)-associated variants and susceptibility to POMS.MethodsCases with onset

ObjectiveEpigenetic modifications have previously been associated with rheumatoid arthritis (RA). In this study, we aimed to determine whether differential DNA methylation in peripheral blood cell subpopulations is associated with any of 4 clinical outcomes among RA patients.MethodsPeripheral blood samples were obtained from 63 patients in the University of California, San Francisco RA cohort (all satisfied the American College of Rheumatology classification criteria; 57 were seropositive for rheumatoid factor and/or anti-cyclic citrullinated protein). Fluorescence-activated cell sorting was used to separate the cells into 4 immune cell subpopulations (CD14+ monocytes, CD19+ B cells, CD4+ naive T cells, and CD4+ memory T cells) per individual, and 229 epigenome-wide DNA methylation profiles were generated using Illumina HumanMethylation450 BeadChips. Differentially methylated positions and regions associated with the Clinical Disease Activity Index score, erosive disease, RA Articular Damage score, Sharp score, medication at time of blood draw, smoking status, and disease duration were identified using robust regression models and empirical Bayes variance estimators.ResultsDifferential methylation of CpG sites associated with clinical outcomes was observed in all 4 cell types. Hypomethylated regions in the CYP2E1 and DUSP22 gene promoters were associated with active and erosive disease, respectively. Pathway analyses suggested that the biologic mechanisms underlying each clinical outcome are cell type-specific. Evidence of independent effects on DNA methylation from smoking, medication use, and disease duration were also identified.ConclusionMethylation signatures specific to RA clinical outcomes may have utility as biomarkers or predictors of exposure, disease progression, and disease severity.

ObjectiveTo utilize Mendelian randomization to estimate the causal association between low serum vitamin D concentrations, increased body mass index (BMI), and pediatric-onset multiple sclerosis (MS) using genetic risk scores (GRS).MethodsWe constructed an instrumental variable for vitamin D (vitD GRS) by computing a GRS for 3 genetic variants associated with levels of 25(OH)D in serum using the estimated effect of each risk variant. A BMI GRS was also created that incorporates the cumulative effect of 97 variants associated with BMI. Participants included non-Hispanic white individuals recruited from over 15 sites across the United States (n = 394 cases, 10,875 controls) and Sweden (n = 175 cases, 5,376 controls; total n = 16,820).ResultsMeta-analysis findings demonstrated that a vitD GRS associated with increasing levels of 25(OH)D in serum decreased the odds of pediatric-onset MS (odds ratio [OR] 0.72, 95% confidence interval [CI] 0.55, 0.94; p = 0.02) after controlling for sex, genetic ancestry, HLA-DRB1*15:01, and over 100 non-human leukocyte antigen MS risk variants. A significant association between BMI GRS and pediatric disease onset was also demonstrated (OR 1.17, 95% CI 1.05, 1.30; p = 0.01) after adjusting for covariates. Estimates for each GRS were unchanged when considered together in a multivariable model.ConclusionsWe provide evidence supporting independent and causal effects of decreased vitamin D levels and increased BMI on susceptibility to pediatric-onset MS.

ObjectiveTo determine whether differentially methylated CpGs in synovium-derived fibroblast-like synoviocytes (FLS) of patients with rheumatoid arthritis (RA) were also differentially methylated in RA peripheral blood (PB) samples.MethodsFor this study, 371 genome-wide DNA methylation profiles were measured using Illumina HumanMethylation450 BeadChips in PB samples from 63 patients with RA and 31 unaffected control subjects, specifically in the cell subsets of CD14+ monocytes, CD19+ B cells, CD4+ memory T cells, and CD4+ naive T cells.ResultsOf 5,532 hypermethylated FLS candidate CpGs, 1,056 were hypermethylated in CD4+ naive T cells from RA PB compared to control PB. In analyses of a second set of CpG candidates based on single-nucleotide polymorphisms from a genome-wide association study of RA, 1 significantly hypermethylated CpG in CD4+ memory T cells and 18 significant CpGs (6 hypomethylated, 12 hypermethylated) in CD4+ naive T cells were found. A prediction score based on the hypermethylated FLS candidates had an area under the curve of 0.73 for association with RA case status, which compared favorably to the association of RA with the HLA-DRB1 shared epitope risk allele and with a validated RA genetic risk score.ConclusionFLS-representative DNA methylation signatures derived from the PB may prove to be valuable biomarkers for the risk of RA or for disease status.

Multiple sclerosis (MS) is an autoimmune disease with both genetic and environmental risk factors. Recent studies indicate that childhood and adolescent obesity double the risk of MS, but this association may reflect unmeasured confounders rather than causal effects of obesity. We used separate-sample Mendelian randomization to estimate the causal effect of body mass index (BMI) on susceptibility to MS. Using data from non-Hispanic white members of the Kaiser Permanente Medical Care Plan of Northern California (KPNC) (2006-2014; 1,104 cases of MS and 10,536 controls) and a replication data set from Sweden (the Epidemiological Investigation of MS (EIMS) and the Genes and Environment in MS (GEMS) studies, 2005-2013; 5,133 MS cases and 4,718 controls), we constructed a weighted genetic risk score using 97 variants previously established to predict BMI. Results were adjusted for birth year, sex, education, smoking status, ancestry, and genetic predictors of MS. Estimates in KPNC and Swedish data sets suggested that higher genetically induced BMI predicted greater susceptibility to MS (odds ratio = 1.13, 95% confidence interval: 1.04, 1.22 for the KPNC sample; odds ratio = 1.09, 95% confidence interval: 1.03, 1.15 for the Swedish sample). Although the mechanism remains unclear, to our knowledge, these findings support a causal effect of increased BMI on susceptibility to MS for the first time, and they suggest a role for inflammatory pathways that characterize both obesity and the MS disease process.

ObjectiveWe sought to estimate the causal effect of low serum 25(OH)D on multiple sclerosis (MS) susceptibility that is not confounded by environmental or lifestyle factors or subject to reverse causality.MethodsWe conducted mendelian randomization (MR) analyses using an instrumental variable (IV) comprising 3 single nucleotide polymorphisms found to be associated with serum 25(OH)D levels at genome-wide significance. We analyzed the effect of the IV on MS risk and both age at onset and disease severity in 2 separate populations using logistic regression models that controlled for sex, year of birth, smoking, education, genetic ancestry, body mass index at age 18-20 years or in 20s, a weighted genetic risk score for 110 known MS-associated variants, and the presence of one or more HLA-DRB1*15:01 alleles.ResultsFindings from MR analyses using the IV showed increasing levels of 25(OH)D are associated with a decreased risk of MS in both populations. In white, non-Hispanic members of Kaiser Permanente Northern California (1,056 MS cases and 9,015 controls), the odds ratio (OR) was 0.79 (p = 0.04, 95% confidence interval (CI): 0.64-0.99). In members of a Swedish population from the Epidemiological Investigation of Multiple Sclerosis and Genes and Environment in Multiple Sclerosis MS case-control studies (6,335 cases and 5,762 controls), the OR was 0.86 (p = 0.03, 95% CI: 0.76-0.98). A meta-analysis of the 2 populations gave a combined OR of 0.85 (p = 0.003, 95% CI: 0.76-0.94). No association was observed for age at onset or disease severity.ConclusionsThese results provide strong evidence that low serum 25(OH)D concentration is a cause of MS, independent of established risk factors.

UnlabelledTwo new tools on the UCSC Genome Browser web site provide improved ways of combining information from multiple datasets, optionally including the user's own custom track data and/or data from track hubs. The Data Integrator combines columns from multiple data tracks, showing all items from the first track along with overlapping items from the other tracks. The Variant Annotation Integrator is tailored to adding functional annotations to variant calls; it offers a more restricted set of underlying data tracks but adds predictions of each variant's consequences for any overlapping or nearby gene transcript. When available, it optionally adds additional annotations including effect prediction scores from dbNSFP for missense mutations, ENCODE regulatory summary tracks and conservation scores.Availability and implementationThe web tools are freely available at http://genome.ucsc.edu/ and the underlying database is available for download at http://hgdownload.cse.ucsc.edu/ The software (written in C and Javascript) is available from https://genome-store.ucsc.edu/ and is freely available for academic and non-profit usage; commercial users must obtain a license.Contactangie@soe.ucsc.eduSupplementary informationSupplementary data are available at Bioinformatics online.

The University of California Santa Cruz (UCSC) Genome Browser (http://genome.ucsc.edu) offers online public access to a growing database of genomic sequence and annotations for a large collection of organisms, primarily vertebrates, with an emphasis on the human and mouse genomes. The Browser's web-based tools provide an integrated environment for visualizing, comparing, analysing and sharing both publicly available and user-generated genomic data sets. As of September 2013, the database contained genomic sequence and a basic set of annotation 'tracks' for ∼90 organisms. Significant new annotations include a 60-species multiple alignment conservation track on the mouse, updated UCSC Genes tracks for human and mouse, and several new sets of variation and ENCODE data. New software tools include a Variant Annotation Integrator that returns predicted functional effects of a set of variants uploaded as a custom track, an extension to UCSC Genes that displays haplotype alleles for protein-coding genes and an expansion of data hubs that includes the capability to display remotely hosted user-provided assembly sequence in addition to annotation data. To improve European access, we have added a Genome Browser mirror (http://genome-euro.ucsc.edu) hosted at Bielefeld University in Germany.